Github user srowen commented on a diff in the pull request:
https://github.com/apache/spark/pull/17556#discussion_r110375319
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/tree/impl/RandomForest.scala ---
@@ -1009,10 +1009,24 @@ private[spark] object RandomForest extends Logging {
// sort distinct values
val valueCounts = valueCountMap.toSeq.sortBy(_._1).toArray
+ def weightedMean(pre: (Double, Int), cru: (Double, Int)): Double = {
+ val (preValue, preCount) = pre
+ val (curValue, curCount) = cru
+ (preValue * preCount + curValue * curCount) / (preCount + curCount)
+ }
+
// if possible splits is not enough or just enough, just return all
possible splits
val possibleSplits = valueCounts.length - 1
- if (possibleSplits <= numSplits) {
- valueCounts.map(_._1).init
+ if (possibleSplits == 0) {
+ // constant feature
+ Array.empty[Double]
+
+ } else if (possibleSplits <= numSplits) {
+ valueCounts
+ .sliding(2)
+ .map{x => weightedMean(x(0), x(1))}
--- End diff --
Nit: use () instead of {}
There are more efficient ways of writing this but not as compact. I think
it's OK unless someone suggests this is performance critical here
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have this feature
enabled and wishes so, or if the feature is enabled but not working, please
contact infrastructure at infrastruct...@apache.org or file a JIRA ticket
with INFRA.
---
---------------------------------------------------------------------
To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org
For additional commands, e-mail: reviews-h...@spark.apache.org
